PKPei-Cing Ke

Pei-Cing Ke

*This is an algorithmically generated author record based on publicly available information.

Current Organizations / Institutes

The organizations/institutes from the scholar's latest article


Pei-Cing Ke has a total of 6 co-authors. Here are the top co-authors by number of shared publications:


Latest Publications

  • Open Access

    Prediction of Surgical Outcome by Tumor Volume Doubling Time via Stereo Imaging Software in Early Non-Small Cell Lung Cancer

    by Chia-Chi Liu, Ya-Fu Cheng, Pei-Cing Ke, Yi-Ling Chen, Ching-Min Lin, Bing-Yen Wang

    Background: Volume doubling time (VDT) has been proven to be a powerful predictor of lung cancer progression. In non-small cell lung cancer patients receiving sublobar resection, the discussion of correlation between VDT and surgery was absent. We proposed to investigate the surgical outcomes according to VDT. Methods: We retrospectively studied 96 cases post sublobar resection from 2012 to 2018, collecting two chest CT scans preoperatively of each case and calculating the VDT. The receiver operating characteristic curve was constructed to identify the optimal cut-off point of VDTs as 133 days. We divided patients into two groups: VDT < 133 days and VDT ≥ 133 days. Univariable and multivariable analyses were performed for comparative purposes. Results: Univariable and multivariable analyses revealed that the consolidation and tumor diameter ratio was the factor of overall survival (OS), and VDT was the only factor of disease-free survival (DFS). The five year OS rates of patients with VDTs ≥ 133 days and VDTs < 133 days, respectively, were 89.9% and 71.9%, and the five year DFS rates were 95.9% and 61.5%. Conclusion: As VDT serves as a powerful prognostic predictor and provides an essential role in planning surgical procedures, the evaluation of VDT preoperatively is highly suggested.


  • Open Access

    Size Measurement and Segmentectomy Resection Margin of Early-Stage Lung Adenocarcinoma Manifesting on Virtual 3D Imagery and Pathology: A Pilot Correlation Study

    by Ching-Min Lin, Hui-Chun Tai, Ya-Fu Cheng, Pei-Cing Ke, Chia-Chi Liu, Bing-Yen Wang

    Background: The objective of our study was to assess if 3D reconstructed images could be extrapolated to reflect pathologies, as evaluated by early-stage lung adenocarcinoma tumor size and simulated segmentectomy resection margin. Methods: Retrospectively selected patients (n = 18) who underwent segmentectomy at Changhua Christian Hospital between 2012 and 2018 and then had pulmonary 3D reconstruction using Ziostation2 were included in our study. Tumor size and simulated segmentectomy resection distance on a 3D model were measure and compared to pathology. Results: Both tumor size and segmentectomy resection margin showed positive correlations between 3D image measurements and pathological measurements. The resection margin showed a stronger correlation and was beneficial in pre-operative planning. Conclusions: A 3D reconstructed model aided understanding of pulmonary anatomy, prompting confidence in surgical approaches and ensured segmentectomy outcome success. Regardless of age and pulmonary function, 3D simulation can accurately mimic segmentectomy, making it a simple, effective and feasible pre-operative planning tool.